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dc.contributor.author | Calatayud-Gregori, Julia | es_ES |
dc.contributor.author | Cortés, J.-C. | es_ES |
dc.contributor.author | Jornet-Sanz, Marc | es_ES |
dc.date.accessioned | 2020-03-31T06:46:09Z | |
dc.date.available | 2020-03-31T06:46:09Z | |
dc.date.issued | 2019-11-30 | es_ES |
dc.identifier.issn | 0170-4214 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/139840 | |
dc.description.abstract | [EN] This paper deals with the randomized heat equation defined on a general bounded interval [L-1, L-2] and with nonhomogeneous boundary conditions. The solution is a stochastic process that can be related, via changes of variable, with the solution stochastic process of the random heat equation defined on [0,1] with homogeneous boundary conditions. Results in the extant literature establish conditions under which the probability density function of the solution process to the random heat equation on [0,1] with homogeneous boundary conditions can be approximated. Via the changes of variable and the Random Variable Transformation technique, we set mild conditions under which the probability density function of the solution process to the random heat equation on a general bounded interval [L-1, L-2] and with nonhomogeneous boundary conditions can be approximated uniformly or pointwise. Furthermore, we provide sufficient conditions in order that the expectation and the variance of the solution stochastic process can be computed from the proposed approximations of the probability density function. Numerical examples are performed in the case that the initial condition process has a certain Karhunen-Loeve expansion, being Gaussian and non-Gaussian. | es_ES |
dc.description.sponsorship | This work has been supported by Spanish Ministerio de Economía y Competitividad grant MTM2017 89664 P. The author Marc Jornet acknowledges the doctorate scholarship granted by Programa de Ayudas de Investigación y Desarrollo (PAID), Universitat Politècnica de València. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | John Wiley & Sons | es_ES |
dc.relation.ispartof | Mathematical Methods in the Applied Sciences | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Karhunen-Loeve expansion | es_ES |
dc.subject | Numerical simulations | es_ES |
dc.subject | Probability density function | es_ES |
dc.subject | Random heat equation | es_ES |
dc.subject | Uncertainty quantification | es_ES |
dc.subject.classification | MATEMATICA APLICADA | es_ES |
dc.title | Uncertainty quantification for random parabolic equations with non-homogeneous boundary conditions on a bounded domain via the approximation of the probability density function | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1002/mma.5333 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2017-89664-P/ES/PROBLEMAS DINAMICOS CON INCERTIDUMBRE SIMULABLE: MODELIZACION MATEMATICA, ANALISIS, COMPUTACION Y APLICACIONES/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada | es_ES |
dc.description.bibliographicCitation | Calatayud-Gregori, J.; Cortés, J.; Jornet-Sanz, M. (2019). Uncertainty quantification for random parabolic equations with non-homogeneous boundary conditions on a bounded domain via the approximation of the probability density function. Mathematical Methods in the Applied Sciences. 42(17):5649-5667. https://doi.org/10.1002/mma.5333 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1002/mma.5333 | es_ES |
dc.description.upvformatpinicio | 5649 | es_ES |
dc.description.upvformatpfin | 5667 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 42 | es_ES |
dc.description.issue | 17 | es_ES |
dc.relation.pasarela | S\368936 | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |
dc.contributor.funder | Universitat Politècnica de València | es_ES |
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